1. Field of the Invention
The present invention is directed to investment-portfolio assessment.
2. Background Information
Many analytical tools have been developed to help improve portfolio performance. Some, which are not the focus of the invention to be described below, deal with trading. Such tools come into play after a decision has been made to buy or sell a given asset. An essential goal of trading is to buy or sell that asset in such a manner that one's own actions do not affect the traded asset's market price. An effective trade, in concept, would occur at a price equal to what the market price would have been in the absence of the trade. Algorithmic trading is one example of several existing methods used to diffuse trades in such a manner as to minimize or eliminate adverse price impacts.
Distinct from trading, which presupposes decisions to buy and sell, is the portfolio-management domain, to which the invention below is directed, where the decisions about which assets to buy and sell are made. Managing a portfolio of financial assets may involve many theories and principles in finance and practices from investment management. Generally, a portfolio manager gathers asset data, current market-trend data, portfolio-performance data, and the like and analyzes the gathered data to make various determinations. One such determination is the current rate of return being achieved on portfolio assets. Other determinations may be measures of portfolio risk, tradeoffs between alternative assets, measures of how well strategic goals are being met, and estimates of future performance.
Currently there are many software programs that serve as analytical tools for the portfolio manager (as well as for the asset manager, fund administrator, and the like). There are various services, pertinent timely publications, and other resources for assisting in the foregoing analyses. Examples include attribution analysis, risk analysis, post-implementation analysis, asset-allocation models, portfolio optimizers, and the like. These systems and services provide information regarding how past performance was achieved, or they provide context in which to make decisions about new investment activity. What most distinguishes these systems from most embodiments of the invention to be described below is that their primary result is the evaluation of past, current, or future performance of specific assets individually. So they affect or evaluate what is referred to as strategic decisions: which specific assets to buy and which assets to sell. Risk analyzers, portfolio strategizers, and some other existing software systems can provide simulations of likely portfolio performance, using forecasting methods that evaluate estimated future outcomes. Other analytic systems recast theoretical portfolios in accordance with historical market information and rules for asset selection to evaluate the effectiveness of hypothetical or alternative portfolio-construction strategies (i.e., methods for selecting assets).
Although such tools are helpful in devising portfolio strategy in a rational way, it has been recognized that the strategy thus set and the trading operations used in response do not alone determine the portfolio's performance. Extensive research and experimentation have shown that it is also affected by aspects of day-to-day portfolio management that are particularly vulnerable to irrational and non-optimizing decision-making.
Such decision-making tends to occur, for example, in connection with moving assets into and out of the portfolio to accommodate investors' contributions and withdrawals. For instance, the objective of selling off 5% of a portfolio can be accomplished through any number of tactics. The portfolio manager can sell 5% of each asset position or sell all or most of a few assets that add up to 5% of the portfolio. The manager can also choose to reach this objective by selling assets owned the longest or assets whose market value is above or below their purchase price.
The choice of tactics to use in buying assets is similarly broad. A manager who is trying to increase the portfolio's exposure to an economic sector (e.g., biomedical, banking, technology, etc.), for example, can spread out the purchase across all assets comprising the sector, concentrate the purchase in a few sector assets, or meet the goal by buying only one asset in the sector. Selection of the approach may depend on many factors, not all of which are consistent with traditional economic theory.
The understanding of tactical biases that tend to drive such selections is an extension of work done over the past thirty years in the academic area known as behavioral economics or behavioral finance. Behavioral economics is the intersection of psychology and economics. Emotions, ignorance, and faulty cognition work to make human decision making fall short of the purely rational model. This research indicates that highly trained, professional investment managers fall prey to these same biases. Biases routinely drive tactical portfolio-investment decisions, and their impact is, in all likelihood, non-optimizing, largely unintended, and certainly unexamined or unmeasured. Yet these unexamined biases regularly affect the performance of tens of thousands of professionally managed investment portfolios.
Among the types of bias that have been observed is the propensity to favor selling appreciated assets rather than those that have depreciated. This preference for selling winners over losers does not, in any systematic way, have much to do with which assets may perform better in the future. Empirical research instead suggests that this type of behavior, referred to in economic literature as the “disposition effect,” is non-optimizing and may be motivated by the desire to experience the emotional pleasure of locking in a win while avoiding the unpleasant realization of a loss. A second example of investor bias involves the predisposition to buy assets that were previously owned and sold at a gain. Such a bias, referred to as contra-positive investing, is based entirely on subjective factors and reflects no objective criteria regarding the familiar asset's expected future performance relative to less-familiar ones. In both cases the biased decision is neither reflective of a portfolio strategy nor germane to realizing effective trading.
Although such biases certainly affect the quantities that existing software systems measure, those quantities tend not to be well suited to helping portfolio managers focus on them or on others of the portfolio performance's more-tactical aspects.